Evidence map›Paper›PMID 37253013›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2023

Escalated police stops of Black men are linguistically and psychologically distinct in their earliest moments.

Eugenia H Rho, Maggie Harrington, Yuyang Zhong, Reid Pryzant, Nicholas P Camp, Dan Jurafsky, Jennifer L Eberhardt

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. SPEECH RECOGNITION FOR ANALYSIS OF POLICE RADIO COMMUNICATION.SLT ... : ... IEEE Workshop on Spoken Language Technology : proceedings. IEEE Workshop on Spoken Language Technology · 2024
    Article
  3. Race and Privacy in Broadcast Police Communications.Proceedings of the ACM on human-computer interaction · 2024
    Article
  4. Article
  5. Escalated police stops of Black men are linguistically and psychologically distinct in their earliest moments.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Eugenia H RhoDepartment of Computer Science, Virginia Tech, Blacksburg, VA 24061.ORCID 0000-0002-0961-4397
Maggie HarringtonDepartment of Psychology, Stanford University, Stanford, CA 94305.
Yuyang ZhongDepartment of Organizational Studies, University of Michigan, Ann Arbor, MI 48109.ORCID 0000-0002-8174-1980
Reid PryzantDepartment of Computer Science, Stanford University, Stanford, CA 94305.
Nicholas P CampDepartment of Organizational Studies, University of Michigan, Ann Arbor, MI 48109.
Dan JurafskyDepartment of Computer Science, Stanford University, Stanford, CA 94305.ORCID 0000-0002-6459-7745
Jennifer L EberhardtDepartment of Psychology, Stanford University, Stanford, CA 94305.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Across the United States, police chiefs, city officials, and community leaders alike have highlighted the need to de-escalate police encounters with the public. This concern about escalation extends from encounters involving use of force to routine car stops, where Black drivers are disproportionately pulled over. Yet, despite the calls for action, we know little about the trajectory of police stops or how escalation unfolds. In study 1, we use methods from computational linguistics to analyze police body-worn camera footage from 577 stops of Black drivers. We find that stops with escalated outcomes (those ending in arrest, handcuffing, or a search) diverge from stops without these outcomes in their earliest moments-even in the first 45 words spoken by the officer. In stops that result in escalation, officers are more likely to issue commands as their opening words to the driver and less likely to tell drivers the reason why they are being stopped. In study 2, we expose Black males to audio clips of the same stops and find differences in how escalated stops are perceived: Participants report more negative emotion, appraise officers more negatively, worry about force being used, and predict worse outcomes after hearing only the officer's initial words in escalated versus non-escalated stops. Our findings show that car stops that end in escalated outcomes sometimes begin in an escalated fashion, with adverse effects for Black male drivers and, in turn, police-community relations.

Indexed as

Black or African AmericanLaw EnforcementPoliceEmotionsHumansMaleRacismUnited Statesbody-worn camerasescalationnatural language processing (NLP)policingrace

Identifiers

PMID37253013
PMCPMC10266001

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.